A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm is formulated as a non-cooperative game, where each robot is considered as an agent. Each agent optimizes its own motion and accounts for the predicted movement of surrounding agents. We propose a novel approach to formulate the dynamic collision constraints. Additionally, we account for deadlocks that might occur in a setup of multiple robotic manipulators. We validate our algorithm on a pick and place scenario for four collaborative robots operating in a common workspace in the simulation environment Gazebo. The robots are controlled by the Robot Operating System (ROS). We demonstrate, that our approach is real-time capable and, due to the distributed nature of the approach, easily scales to an arbitrary number of robot manipulators in a shared workspace.
翻译:在一个共享的工作空间中,多机器人操纵器的灵活操作需要在线轨迹规划,静态和动态避免碰撞。在这项工作中,我们提议基于非线性模型预测控制,采用实时功能运动控制算法,其中考虑到静态和动态避免碰撞的情况。提议的算法是一个不合作的游戏,其中每个机器人都被视为一个代理人。每个代理人都优化自己的动作,并记录周围物剂的预期移动情况。我们提议一种新颖的方法来制定动态碰撞限制。此外,我们考虑到在多机器人操纵器的设置中可能出现的僵局。我们验证了在模拟环境中在共同工作空间运行的四个协作机器人的选取和位置。机器人由机器人操作系统控制。我们证明,我们的方法是实时的,由于方法的分布性质,很容易在共同工作空间中将机器人操纵器任意分配给一个数目。